Big Data Demands: The Heightened Need For Advanced Data Visualization

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Seeing is believing, they say, and a picture is worth a thousand words.

Developers of business intelligence and data analytics applications are increasingly using advanced data visualization technology to handle huge volumes of data in a way that helps information workers better interpret analytical results.

"There are a lot of businesses that are being bombarded with data and they need to quickly turn that data into business decisions," said Steve Adams, managing director of the U.K. operations of Linalis, a Geneva, Switzerland-based IT services company that develops business intelligence solutions.

And while most traditional business intelligence tools are geared toward either market analysts or a select few decision makers, advanced data visualization is seen as a way to make business analytics available to a wider audience.

"It's about empowering the end-user to be more self-sufficient," said Dan Potter, IBM product marketing executive who manages Cognos Insight, a "data discovery" exploration and visualization tool IBM debuted in March. "Visualization technology is a big part of that." Advanced data visualization, he said, is "one of the fastest growing areas in business analytics."

ADV "identifies trends and relationships in the data that are not always easy to spot," said Michael Corcoran, chief marketing officer at Information Builders. "I see a broad appeal for many business users who want access to these capabilities."

Limitations inherent in older data presentation applications make it difficult for users to spot patterns and trends, according to the Forrester report. Often they can't fit more than a few thousand data points on a screen, for example, and are generally limited to a few dimensions or attributes, such as time, regions, products, etc.

ADV systems can present information with many -- even dozens -- of dimensions or attributes. Some offer animated visualizations to show, say, changes in sales of a product over a period of time rather than requiring a user to click through a series of charts. Analytical results can be displayed in a three-dimensional graph, a series of "cockpit gauges," a heat map that uses varying colors to represent values or geospatial representations that overlay data on geographical maps.

And, ADV tools are far more interactive. Users can visually query the data by manipulating portions of graphs or charts, the report said, by changing, for example, a dimension such as time to look at analytical results in different timeframes. Or, they can "lasso" a subset of the data to drill down into one segment of the results.

ADV tools are often linked to data sources so that analytical results are dynamically updated as data changes -- a critical feature in such industries as financial services and equities trading in which users are analyzing constant streams of information.